Robust control of a class of neural networks with bounded uncertainties and time-varying delays

被引：12

作者：

Cheng, Chao-Jung ^{[1
]}

机构：

[1] Kun Shan Univ, Dept Informat Engn, Tainan 710, Taiwan

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 2008年 / 56卷 / 05期

关键词：

variable structure control; Cohen-Grossberg neural networks; cellular neural networks; Hopfield neural networks;

D O I：

10.1016/j.camwa.2008.03.012

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper investigates the robust control problem for a class of neural networks subject to bounded uncertainties and time-varying delays. A memoryless decentralized variable structure control law with dead-zone input for guaranteeing global asymptotical system stability is derived. The results demonstrate that the derived control law does not restrict the derivative of the time-varying delays even if dead-zone nonlinearity occurs in the control input. Such a control law can be used to stabilize Cohen-Grossberg neural networks, cellular neural networks and Hopfield neural networks; all of which have bounded uncertainties and time-varying delays. Two examples are provided to illustrate the effectiveness and validity of the proposed control scheme. (c) 2008 Elsevier Ltd. All rights reserved.

引用

页码：1245 / 1254

页数：10

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